Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds
Nunes-Nesi, Adriano ; Alseekh, Saleh ; Oliveira Silva, Franklin Magnum de; Omranian, Nooshin ; Lichtenstein, Gabriel ; Mirnezhad, Mohammad ; González, Roman R.R. ; y Garcia, Julia Sabio ; Conte, Mariana ; Leiss, Kirsten A. ; Klinkhamer, Peter G.L. ; Nikoloski, Zoran ; Carrari, Fernando ; Fernie, Alisdair R. - \ 2019
Metabolomics 15 (2019)4. - ISSN 1573-3882
Leaf metabolism - Metabolite network - Metabolite QTL - Tomato

Introduction: To date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism. Objective: This study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues. Methods: The analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses. Results: Changes in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism. Conclusions: Overall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.

Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions
Wu, Si ; Tohge, Takayuki ; Cuadros-Inostroza, Álvaro ; Tong, Hao ; Tenenboim, Hezi ; Kooke, Rik ; Méret, Michaël ; Keurentjes, Joost B. ; Nikoloski, Zoran ; Fernie, Alisdair Robert ; Willmitzer, Lothar ; Brotman, Yariv - \ 2018
Molecular Plant 11 (2018)1. - ISSN 1674-2052 - p. 118 - 134.
Different environments - GWAS - Network analysis - Secondary metabolism - Untargeted metabolomics

Metabolic genome-wide association studies (mGWAS), whereupon metabolite levels are regarded as traits, can help unravel the genetic basis of metabolic networks. A total of 309 Arabidopsis accessions were grown under two independent environmental conditions (control and stress) and subjected to untargeted LC-MS-based metabolomic profiling; levels of the obtained hydrophilic metabolites were used in GWAS. Our two-condition-based GWAS for more than 3000 semi-polar metabolites resulted in the detection of 123 highly resolved metabolite quantitative trait loci (p ≤ 1.0E-08), 24.39% of which were environment-specific. Interestingly, differently from natural variation in Arabidopsis primary metabolites, which tends to be controlled by a large number of small-effect loci, we found several major large-effect loci alongside a vast number of small-effect loci controlling variation of secondary metabolites. The two-condition-based GWAS was followed by integration with network-derived metabolite-transcript correlations using a time-course stress experiment. Through this integrative approach, we selected 70 key candidate associations between structural genes and metabolites, and experimentally validated eight novel associations, two of them showing differential genetic regulation in the two environments studied. We demonstrate the power of combining large-scale untargeted metabolomics-based GWAS with time-course-derived networks both performed under different abiotic environments for identifying metabolite-gene associations, providing novel global insights into the metabolic landscape of Arabidopsis. By combining large-scale untargeted metabolomics-based GWAS and network analysis with environmental stress-driven perturbations of metabolic homeostasis, this system-wide study provides new global insights into the metabolic landscape of Arabidopsis, using a strategy that could readily be extended to other plant species.

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